{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m2025-05-15 14:46:21.385\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36m__main__\u001b[0m:\u001b[36m<module>\u001b[0m:\u001b[36m14\u001b[0m - \u001b[1m文件读取成功\u001b[0m\n",
      "\u001b[32m2025-05-15 14:46:21.385\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36m__main__\u001b[0m:\u001b[36m<module>\u001b[0m:\u001b[36m15\u001b[0m - \u001b[1m      实例       算法  迭代次数                                                  解  \\\n",
      "0   Du62  RL+遗传算法   620  [[33, 4, 23, 18, 62, 40, 13, 6], [51, 22, 34, ...   \n",
      "1   Du62  RL+遗传算法   620  [[48, 46, 49, 15, 58, 37, 17], [54, 42, 52, 27...   \n",
      "2   Du62  RL+遗传算法   620  [[17, 51, 41, 40, 37, 9, 15], [14, 8, 49, 18, ...   \n",
      "3   Du62  RL+遗传算法   620  [[9, 26, 8, 45, 39, 33, 17], [31, 12, 50, 30, ...   \n",
      "4   Du62  RL+遗传算法   620  [[7, 54, 22, 41, 19, 6, 13], [39, 49, 40, 4, 3...   \n",
      "5   Du62  RL+遗传算法   620  [[17, 55, 45, 34, 62, 10, 48], [33, 36, 23, 38...   \n",
      "6   Du62  RL+遗传算法   620  [[15, 9, 24, 23, 28, 6, 17], [46, 5, 18, 57, 1...   \n",
      "7   Du62  RL+遗传算法   620  [[14, 7, 49, 46, 9, 54, 15, 48], [39, 42, 44, ...   \n",
      "8   Du62  RL+遗传算法   620  [[46, 9, 31, 37, 26, 4, 14], [7, 22, 49, 44, 4...   \n",
      "9   Du62  RL+遗传算法   620  [[9, 14, 62, 22, 26, 45, 7], [46, 10, 12, 50, ...   \n",
      "10  Du62  RL+遗传算法   620  [[14, 15, 9, 18, 19, 10, 33, 17], [49, 55, 44,...   \n",
      "11  Du62  RL+遗传算法   620  [[9, 46, 39, 49, 24, 45, 55, 15], [44, 40, 5, ...   \n",
      "12  Du62  RL+遗传算法   620  [[15, 48, 58, 62, 38, 42, 6, 17], [51, 31, 27,...   \n",
      "13  Du62  RL+遗传算法   620  [[10, 55, 1, 24, 34, 13, 33], [54, 8, 18, 41, ...   \n",
      "14  Du62  RL+遗传算法   620  [[48, 6, 30, 53, 60, 41, 45], [13, 19, 22, 18,...   \n",
      "15  Du62  RL+遗传算法   620  [[6, 7, 13, 35, 1, 23, 45], [41, 29, 44, 53, 1...   \n",
      "16  Du62  RL+遗传算法   620  [[14, 41, 4, 51, 54, 53, 7], [15, 29, 11, 58, ...   \n",
      "17  Du62  RL+遗传算法   620  [[15, 14, 53, 49, 33, 48, 7], [45, 44, 47, 20,...   \n",
      "18  Du62  RL+遗传算法   620  [[62, 14, 41, 3, 24, 32, 15, 6], [54, 23, 28, ...   \n",
      "19  Du62  RL+遗传算法   620  [[14, 54, 9, 47, 33, 39, 7], [48, 22, 59, 18, ...   \n",
      "20  Du62  RL+遗传算法  1860  [[6, 33, 45, 39, 51, 26, 9, 17], [4, 8, 30, 35...   \n",
      "21  Du62  RL+遗传算法  1860  [[17, 33, 22, 55, 34, 45, 7], [13, 23, 24, 12,...   \n",
      "22  Du62  RL+遗传算法  1860  [[7, 54, 39, 19, 33, 9, 17], [53, 49, 47, 52, ...   \n",
      "23  Du62  RL+遗传算法  1860  [[17, 45, 33, 49, 39, 26, 15], [9, 34, 38, 23,...   \n",
      "24  Du62  RL+遗传算法   620  [[14, 45, 39, 4, 23, 10, 6], [22, 3, 57, 28, 4...   \n",
      "25  Du62  RL+遗传算法  3844  [[13, 33, 39, 34, 7, 48, 15], [41, 22, 50, 47,...   \n",
      "26  Du62  RL+遗传算法  3844  [[6, 48, 62, 53, 54, 31, 15], [13, 35, 2, 59, ...   \n",
      "27  Du62  RL+遗传算法  3844  [[45, 19, 55, 34, 23, 13, 17], [4, 58, 36, 35,...   \n",
      "28  Du62  RL+遗传算法  3844  [[6, 7, 41, 49, 25, 39, 33], [19, 4, 40, 5, 51...   \n",
      "29  Du62  RL+遗传算法  3844  [[15, 48, 58, 34, 42, 13, 6], [33, 22, 8, 36, ...   \n",
      "30  Du62  RL+遗传算法  3844  [[15, 14, 10, 36, 55, 34, 62], [6, 13, 42, 27,...   \n",
      "31  Du62  RL+遗传算法  3844  [[15, 13, 35, 34, 19, 33, 6], [46, 42, 53, 36,...   \n",
      "32  Du62  RL+遗传算法  3844  [[48, 7, 33, 51, 9, 22, 39, 14], [62, 35, 11, ...   \n",
      "33  Du62  RL+遗传算法  3844  [[15, 46, 55, 24, 23, 54, 14], [6, 44, 27, 28,...   \n",
      "34  Du62  RL+遗传算法  3844  [[15, 46, 54, 58, 4, 6, 17], [13, 25, 40, 32, ...   \n",
      "35  Du62  RL+遗传算法  3844  [[17, 33, 39, 25, 49, 62, 9, 14], [26, 51, 50,...   \n",
      "36  Du62  RL+遗传算法  3844  [[17, 14, 10, 39, 55, 45, 6], [7, 49, 57, 25, ...   \n",
      "37  Du62  RL+遗传算法  3844  [[17, 62, 55, 34, 10, 13, 6], [45, 23, 1, 42, ...   \n",
      "38  Du62  RL+遗传算法  3844  [[7, 48, 51, 42, 54, 33, 15], [39, 49, 25, 47,...   \n",
      "39  Du62  RL+遗传算法  3844  [[15, 7, 13, 48, 31, 6, 17], [10, 49, 11, 42, ...   \n",
      "40  Du62  RL+遗传算法  3844  [[9, 14, 47, 7, 53, 48, 15], [46, 49, 44, 29, ...   \n",
      "41  Du62  RL+遗传算法  3844  [[17, 15, 58, 19, 55, 10, 6], [33, 8, 18, 30, ...   \n",
      "42  Du62  RL+遗传算法  3844  [[6, 13, 42, 48, 31, 7, 15], [62, 36, 35, 52, ...   \n",
      "43  Du62  RL+遗传算法  3844  [[19, 14, 54, 40, 62, 33, 17], [10, 30, 32, 38...   \n",
      "44  Du62  RL+遗传算法  3844  [[15, 62, 42, 31, 19, 13, 6], [48, 10, 57, 40,...   \n",
      "\n",
      "            适应度值                    开始时间                    最快时间  \\\n",
      "0   3.859403e+06 2025-04-24 10:32:01.003 2025-04-24 10:33:37.081   \n",
      "1   3.892279e+06 2025-04-24 10:33:40.868 2025-04-24 10:35:15.566   \n",
      "2   3.939824e+06 2025-04-24 10:35:22.020 2025-04-24 10:36:59.247   \n",
      "3   3.821024e+06 2025-04-24 10:37:03.396 2025-04-24 10:38:39.698   \n",
      "4   3.904598e+06 2025-04-24 10:38:44.914 2025-04-24 10:40:19.401   \n",
      "5   3.862892e+06 2025-04-24 10:40:26.232 2025-04-24 10:42:04.298   \n",
      "6   3.886810e+06 2025-04-24 10:42:08.099 2025-04-24 10:43:46.344   \n",
      "7   3.903910e+06 2025-04-24 10:43:50.258 2025-04-24 10:45:28.590   \n",
      "8   3.884119e+06 2025-04-24 10:45:32.733 2025-04-24 10:47:07.709   \n",
      "9   3.923774e+06 2025-04-24 10:47:13.381 2025-04-24 10:48:47.580   \n",
      "10  3.875304e+06 2025-04-24 10:48:53.759 2025-04-24 10:50:28.888   \n",
      "11  3.923527e+06 2025-04-24 10:50:33.253 2025-04-24 10:52:02.166   \n",
      "12  3.867018e+06 2025-04-24 10:52:12.434 2025-04-24 10:53:46.520   \n",
      "13  3.882603e+06 2025-04-24 10:53:52.858 2025-04-24 10:55:21.742   \n",
      "14  3.895892e+06 2025-04-24 10:55:33.106 2025-04-24 10:57:03.820   \n",
      "15  3.893490e+06 2025-04-24 10:57:13.882 2025-04-24 11:15:01.905   \n",
      "16  3.899950e+06 2025-04-24 11:15:08.280 2025-04-24 11:16:42.930   \n",
      "17  3.863072e+06 2025-04-24 11:16:48.146 2025-04-24 11:33:28.515   \n",
      "18  3.957802e+06 2025-04-24 11:33:32.596 2025-04-24 11:35:05.420   \n",
      "19  3.883441e+06 2025-04-24 11:35:12.487 2025-04-24 11:36:47.671   \n",
      "20  3.773296e+06 2025-05-13 19:52:04.730 2025-05-13 19:56:37.792   \n",
      "21  3.840034e+06 2025-05-13 19:56:45.814 2025-05-13 20:01:15.364   \n",
      "22  3.810930e+06 2025-05-13 20:01:34.723 2025-05-13 20:06:17.507   \n",
      "23  3.789199e+06 2025-05-13 20:06:28.495 2025-05-13 20:11:15.866   \n",
      "24  3.891816e+06 2025-05-13 21:01:30.349 2025-05-13 21:03:23.043   \n",
      "25  3.745653e+06 2025-05-14 21:21:30.883 2025-05-14 21:26:21.229   \n",
      "26  3.705008e+06 2025-05-14 21:29:55.980 2025-05-14 21:37:57.528   \n",
      "27  3.693278e+06 2025-05-14 21:38:29.736 2025-05-14 22:33:54.358   \n",
      "28  3.725944e+06 2025-05-14 22:35:14.048 2025-05-14 22:43:38.757   \n",
      "29  3.724710e+06 2025-05-14 22:44:04.791 2025-05-14 22:50:22.424   \n",
      "30  3.734534e+06 2025-05-14 22:52:41.793 2025-05-14 23:49:30.717   \n",
      "31  3.722898e+06 2025-05-14 23:49:51.026 2025-05-14 23:58:53.886   \n",
      "32  3.725190e+06 2025-05-15 00:17:58.360 2025-05-15 00:44:33.283   \n",
      "33  3.759034e+06 2025-05-15 00:44:59.342 2025-05-15 01:43:10.242   \n",
      "34  3.756104e+06 2025-05-15 01:43:27.875 2025-05-15 01:49:34.386   \n",
      "35  3.694483e+06 2025-05-15 02:12:11.070 2025-05-15 02:38:41.717   \n",
      "36  3.716317e+06 2025-05-15 02:40:09.124 2025-05-15 03:18:08.587   \n",
      "37  3.675102e+06 2025-05-15 03:19:29.241 2025-05-15 04:25:56.467   \n",
      "38  3.753980e+06 2025-05-15 04:27:42.762 2025-05-15 04:37:43.018   \n",
      "39  3.741501e+06 2025-05-15 05:10:00.524 2025-05-15 05:58:00.115   \n",
      "40  3.721691e+06 2025-05-15 06:01:10.566 2025-05-15 06:26:58.474   \n",
      "41  3.725221e+06 2025-05-15 06:29:54.904 2025-05-15 07:28:34.372   \n",
      "42  3.733760e+06 2025-05-15 07:28:53.492 2025-05-15 07:36:50.082   \n",
      "43  3.739481e+06 2025-05-15 07:56:06.206 2025-05-15 08:02:09.176   \n",
      "44  3.760546e+06 2025-05-15 08:04:34.690 2025-05-15 08:10:45.764   \n",
      "\n",
      "                      结束时间         运行时间     最快最佳结果时间                 备注  \\\n",
      "0  2025-04-24 10:33:37.091    96.087905    96.078302     K分初始解v3-奖励函数v2   \n",
      "1  2025-04-24 10:35:18.305    97.436903    94.697568     K分初始解v3-奖励函数v2   \n",
      "2  2025-04-24 10:36:59.597    97.577082    97.226939     K分初始解v3-奖励函数v2   \n",
      "3  2025-04-24 10:38:41.152    97.755597    96.302167     K分初始解v3-奖励函数v2   \n",
      "4  2025-04-24 10:40:22.471    97.557547    94.486907     K分初始解v3-奖励函数v2   \n",
      "5  2025-04-24 10:42:04.308    98.075933    98.065978     K分初始解v3-奖励函数v2   \n",
      "6  2025-04-24 10:43:46.548    98.449075    98.245612     K分初始解v3-奖励函数v2   \n",
      "7  2025-04-24 10:45:28.933    98.675261    98.331590     K分初始解v3-奖励函数v2   \n",
      "8  2025-04-24 10:47:09.594    96.860726    94.976126     K分初始解v3-奖励函数v2   \n",
      "9  2025-04-24 10:48:49.977    96.595420    94.198394     K分初始解v3-奖励函数v2   \n",
      "10 2025-04-24 10:50:29.546    95.787691    95.129197     K分初始解v3-奖励函数v2   \n",
      "11 2025-04-24 10:52:08.663    95.410907    88.913860     K分初始解v3-奖励函数v2   \n",
      "12 2025-04-24 10:53:49.099    96.664863    94.085600     K分初始解v3-奖励函数v2   \n",
      "13 2025-04-24 10:55:29.328    96.469994    88.883664     K分初始解v3-奖励函数v2   \n",
      "14 2025-04-24 10:57:10.106    97.000023    90.713078     K分初始解v3-奖励函数v2   \n",
      "15 2025-04-24 11:15:04.589  1070.707076  1068.023016     K分初始解v3-奖励函数v2   \n",
      "16 2025-04-24 11:16:44.404    96.123707    94.650386     K分初始解v3-奖励函数v2   \n",
      "17 2025-04-24 11:33:28.827  1000.680376  1000.368759     K分初始解v3-奖励函数v2   \n",
      "18 2025-04-24 11:35:08.785    96.189068    92.824395     K分初始解v3-奖励函数v2   \n",
      "19 2025-04-24 11:36:48.800    96.312956    95.184187     K分初始解v3-奖励函数v2   \n",
      "20 2025-05-13 19:56:42.017   277.286365   273.061268     K分初始解v3-奖励函数v1   \n",
      "21 2025-05-13 20:01:30.954   285.139905   269.549840     K分初始解v3-奖励函数v1   \n",
      "22 2025-05-13 20:06:24.731   290.008239   282.783510     K分初始解v3-奖励函数v1   \n",
      "23 2025-05-13 20:11:22.639   294.144447   287.371945     K分初始解v3-奖励函数v1   \n",
      "24 2025-05-13 21:03:26.484   116.135263   112.693667     K分初始解v3-奖励函数v1   \n",
      "25 2025-05-14 21:29:52.280   501.396639   290.345301  K分初始解v3-奖励函数v1-测试   \n",
      "26 2025-05-14 21:38:26.055   510.074654   481.547579  K分初始解v3-奖励函数v1-测试   \n",
      "27 2025-05-14 22:35:10.213  3400.477505  3324.622558  K分初始解v3-奖励函数v1-测试   \n",
      "28 2025-05-14 22:44:01.012   526.963592   504.708687  K分初始解v3-奖励函数v1-测试   \n",
      "29 2025-05-14 22:52:38.007   513.216257   377.632925  K分初始解v3-奖励函数v1-测试   \n",
      "30 2025-05-14 23:49:47.305  3425.511993  3408.924376  K分初始解v3-奖励函数v1-测试   \n",
      "31 2025-05-15 00:17:54.727  1683.700561   542.859777  K分初始解v3-奖励函数v1-测试   \n",
      "32 2025-05-15 00:44:55.621  1617.260829  1594.923494  K分初始解v3-奖励函数v1-测试   \n",
      "33 2025-05-15 01:43:24.207  3504.864807  3490.899805  K分初始解v3-奖励函数v1-测试   \n",
      "34 2025-05-15 02:12:07.432  1719.557190   366.511400  K分初始解v3-奖励函数v1-测试   \n",
      "35 2025-05-15 02:40:04.050  1672.980215  1590.647335  K分初始解v3-奖励函数v1-测试   \n",
      "36 2025-05-15 03:19:25.491  2356.367064  2279.462514  K分初始解v3-奖励函数v1-测试   \n",
      "37 2025-05-15 04:27:39.015  4089.773798  3987.225906  K分初始解v3-奖励函数v1-测试   \n",
      "38 2025-05-15 05:09:56.767  2534.005305   600.256210  K分初始解v3-奖励函数v1-测试   \n",
      "39 2025-05-15 06:01:05.412  3064.887788  2879.591574  K分初始解v3-奖励函数v1-测试   \n",
      "40 2025-05-15 06:29:49.170  1718.604784  1547.908059  K分初始解v3-奖励函数v1-测试   \n",
      "41 2025-05-15 07:28:49.741  3534.836853  3519.467493  K分初始解v3-奖励函数v1-测试   \n",
      "42 2025-05-15 07:56:02.547  1629.055241   476.590312  K分初始解v3-奖励函数v1-测试   \n",
      "43 2025-05-15 08:04:30.976   504.770007   362.970516  K分初始解v3-奖励函数v1-测试   \n",
      "44 2025-05-15 08:12:58.528   503.837810   371.074023  K分初始解v3-奖励函数v1-测试   \n",
      "\n",
      "     最佳解训练时间(秒)  \n",
      "0     96.078302  \n",
      "1     94.697568  \n",
      "2     97.226939  \n",
      "3     96.302167  \n",
      "4     94.486907  \n",
      "5     98.065978  \n",
      "6     98.245612  \n",
      "7     98.331590  \n",
      "8     94.976126  \n",
      "9     94.198394  \n",
      "10    95.129197  \n",
      "11    88.913860  \n",
      "12    94.085600  \n",
      "13    88.883664  \n",
      "14    90.713078  \n",
      "15  1068.023016  \n",
      "16    94.650386  \n",
      "17  1000.368759  \n",
      "18    92.824395  \n",
      "19    95.184187  \n",
      "20   273.061268  \n",
      "21   269.549840  \n",
      "22   282.783510  \n",
      "23   287.371945  \n",
      "24   112.693667  \n",
      "25   290.345301  \n",
      "26   481.547579  \n",
      "27  3324.622558  \n",
      "28   504.708687  \n",
      "29   377.632925  \n",
      "30  3408.924376  \n",
      "31   542.859777  \n",
      "32  1594.923494  \n",
      "33  3490.899805  \n",
      "34   366.511400  \n",
      "35  1590.647335  \n",
      "36  2279.462514  \n",
      "37  3987.225906  \n",
      "38   600.256210  \n",
      "39  2879.591574  \n",
      "40  1547.908059  \n",
      "41  3519.467493  \n",
      "42   476.590312  \n",
      "43   362.970516  \n",
      "44   371.074023  \u001b[0m\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "from loguru import logger\n",
    "\n",
    "n = 30\n",
    "instance = \"Du62\"\n",
    "algorithm = \"RL+遗传算法\"\n",
    "# file_path = f\"/Users/maoyan/Codes/Python/gym-flp-fbs/Files/ExpResult/{instance}-模拟退火算法1.xlsx\"\n",
    "file_path = f\"/Users/maoyan/Codes/Python/gym-flp-fbs/Files/ExpResult/{instance}-{algorithm}.xlsx\"\n",
    "is_repair = True\n",
    "# 提取数据\n",
    "datas = []\n",
    "df = pd.read_excel(file_path)\n",
    "logger.info(\"文件读取成功\")\n",
    "logger.info(df)\n",
    "plt.rcParams['font.sans-serif'] = ['Arial Unicode MS']  # 或者 ['SimHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False  # 解决负号显示问题\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1200x800 with 0 Axes>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1200x800 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "groups = df.groupby('备注')\n",
    "# 使用不同颜色和线型绘制\n",
    "colors = ['blue', 'red', 'green', 'orange', 'purple', 'brown', 'pink', 'gray']\n",
    "line_styles = ['-', '--', '-.', ':']\n",
    "markers = ['o', 's', '^', 'D', '*', 'x', '+']\n",
    "# 创建一个足够大的图形以容纳标注\n",
    "plt.figure(figsize=(12, 8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m2025-05-14 20:01:17.267\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36m__main__\u001b[0m:\u001b[36m<module>\u001b[0m:\u001b[36m1\u001b[0m - \u001b[1m<pandas.core.groupby.generic.DataFrameGroupBy object at 0x1221e8f70>\u001b[0m\n",
      "\u001b[32m2025-05-14 20:01:17.269\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36m__main__\u001b[0m:\u001b[36m<module>\u001b[0m:\u001b[36m2\u001b[0m - \u001b[1m0\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "logger.info(groups)\n",
    "logger.info(len(groups))\n",
    "for name, group in groups:\n",
    "    logger.info(name)\n",
    "    logger.info(group)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "# 过滤器\n",
    "# 过滤掉group_name 包含随机的\n",
    "# groups = [(group_name, group_df) for group_name, group_df in groups if '随机' not in group_name]\n",
    "\n",
    "# 将每一组的值进行排序\n",
    "# for group_name, group_df in groups:\n",
    "#     # 排序\n",
    "#     group_df.sort_values(by='适应度值', ascending=True, inplace=True)\n",
    "#     # 重新索引\n",
    "#     group_df.reset_index(drop=True, inplace=True)\n",
    "#     # 重新赋值\n",
    "#     groups = [(group_name, group_df) for group_name, group_df in groups if group_name == group_name]\n",
    "\n",
    "\n",
    "for i, (group_name, group_df) in enumerate(groups):\n",
    "    # 创建从1开始的x轴序号\n",
    "    x_values = range(1, len(group_df) + 1)\n",
    "    y_values = group_df.适应度值.values\n",
    "    \n",
    "    color_idx = i % len(colors)\n",
    "    style_idx = i % len(line_styles)\n",
    "    marker_idx = i % len(markers)\n",
    "    \n",
    "    # 绘制折线\n",
    "    plt.plot(x_values, y_values, \n",
    "             label=group_name,\n",
    "             color=colors[color_idx],\n",
    "             linestyle=line_styles[style_idx],\n",
    "             marker=markers[marker_idx],\n",
    "             markersize=6)\n",
    "    \n",
    "    # 在每个点上添加标注\n",
    "    for x, y in zip(x_values, y_values):\n",
    "        plt.annotate(f'{y:.2f}',  # 保留两位小数\n",
    "                    xy=(x, y),  # 点的位置\n",
    "                    xytext=(0, 5),  # 文字与点的相对位置（稍微向上偏移）\n",
    "                    textcoords='offset points',  # 使用偏移坐标\n",
    "                    ha='center',  # 水平居中对齐\n",
    "                    va='bottom',  # 垂直底部对齐\n",
    "                    fontsize=8,  # 字体大小\n",
    "                    color=colors[color_idx])  # 使用与线相同的颜色\n",
    "    \n",
    "# 添加标题和标签\n",
    "plt.title(instance)\n",
    "plt.xlabel('序号')\n",
    "plt.ylabel('适应度值')\n",
    "\n",
    "# 显示图例并优化位置\n",
    "plt.legend(loc='best', frameon=True, fancybox=True, framealpha=0.7)\n",
    "\n",
    "# 添加网格线以便更好地查看\n",
    "plt.grid(True, linestyle='--', alpha=0.7)\n",
    "\n",
    "# 优化图表边距\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "gym-fbs",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
